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Primal-dual approximation algorithms for submodular cost set cover problems with linear/submodular penalties
Complexity analysis of primal-dual interior-point methods for semidefinite optimization based on a parametric kernel function with a trigonometric barrier term
1. | College of Fundamental Studies, Shanghai University of Engineering Science, Shanghai 201620, China, China, China, China |
References:
[1] |
M. Achache and L. Guerra, A full Nesterov-Todd step feasible primal-dual interior-point algorithm for convex quadratic semidefinite optimization,, Applied Mathematics and Computation, 231 (2014), 581.
doi: 10.1016/j.amc.2013.12.070. |
[2] |
Y. Q. Bai, M. El Ghami and C. Roos, A comparative study of kernel functions for primal-dual interior-point algorithms in linear optimization,, SIAM Journal on Optimization, 15 (2004), 101.
doi: 10.1137/S1052623403423114. |
[3] |
X. Z. Cai, G. Q. Wang, M. El Ghami and Y. J. Yue, Complexity analysis of primal-dual interior-point methods for linear optimization based on a parametric kernel function with a trigonometric barrier term,, Abstract and Applied Analysis, 2014 (2014).
doi: 10.1155/2014/710158. |
[4] |
B. K. Choi. and G. M. Lee, On complexity analysis of the primal-dual interior-point method for semidefinite optimization problem based on a new proximity function,, Nonlinear Analysis, 71 (2009), 2628.
doi: 10.1016/j.na.2009.05.078. |
[5] |
Zs. Darvay, New interior point algorithms in linear programming,, Advanced Modeling and Optimization, 5 (2003), 51.
|
[6] |
E. De Klerk, Aspects of Semidefinite Programming: Interior Point Algorithms and Selected Applications,, Kluwer Academic Publishers, (2002).
doi: 10.1007/b105286. |
[7] |
M. El Ghami, Z. A. Guennounb, S. Bouali and T. Steihaug, Interior-point methods for linear optimization based on a kernel function with a trigonometric barrier term,, Journal of Computational and Applied Mathematics, 236 (2012), 3613.
doi: 10.1016/j.cam.2011.05.036. |
[8] |
M. El Ghami, C. Roos and T. Steihaug, A generic primal-dual interior-point method for semidefinite optimization based on a new class of kernel functions,, Optimization Methods & Software, 25 (2010), 387.
doi: 10.1080/10556780903239048. |
[9] |
R. A. Horn and C. R. Johnson, Topics in Matrix Analysis,, Cambridge University Press, (1991).
doi: 10.1017/CBO9780511840371. |
[10] |
B. Kheirfam, Simplified infeasible interior-point algorithm for SDO using full Nesterov-Todd step,, Numerical Algorithms, 59 (2012), 589.
doi: 10.1007/s11075-011-9506-1. |
[11] |
M. Kojima, M. Shida and S. Shindoh, Local convergence of predictor-corrector infeasible-interior-point method for SDPs and SDLCPs,, Mathematical Programming, 80 (1998), 129.
doi: 10.1007/BF01581723. |
[12] |
H. W. Liu, C. H. Liu and X. M. Yang, New complexity analysis of a Mehrotra-type predictor-corrector algorithm for semidefinite programming,, Optimization Methods & Software, 28 (2013), 1179.
doi: 10.1080/10556788.2012.679270. |
[13] |
H. Mansouri and C. Roos, A new full-Newton step O(n) infeasible interior-point algorithm for semidefinite optimization,, Numerical Algorithms, 52 (2009), 225.
doi: 10.1007/s11075-009-9270-7. |
[14] |
J. Peng, C. Roos and T. Terlaky, Self-regular functions and new search directions for linear and semidefinite optimization,, Mathematical Programming, 93 (2002), 129.
doi: 10.1007/s101070200296. |
[15] |
M. R. Peyghami, An interior-point approach for semidefinite optimization using new proximity functions,, Asia-Pacific Journal of Operational Research, 26 (2009), 365.
doi: 10.1142/S0217595909002250. |
[16] |
M. R. Peyghami and S. F. Hafshejani, Complexity analysis of an interior-point algorithm for linear optimization based on a new proximity function,, Numerical Algorithms, 67 (2014), 33.
doi: 10.1007/s11075-013-9772-1. |
[17] |
M. R. Peyghami, S. F. Hafshejani and L. Shirvani, Complexity of interior-point methods for linear optimization based on a new trigonometric kernel function,, Journal of Computational and Applied Mathematics, 255 (2014), 74.
doi: 10.1016/j.cam.2013.04.039. |
[18] |
C. Roos, T. Terlaky and J.-Ph. Vial, Theory and Algorithms for Linear Optimization,, Springer, (2005). Google Scholar |
[19] |
G. Q. Wang and Y. Q. Bai, A new primal-dual path-following interior-point algorithm for semidefinite optimization,, Journal of Mathematical Analysis and Applications, 353 (2009), 339.
doi: 10.1016/j.jmaa.2008.12.016. |
[20] |
G. Q. Wang, Y. Q. Bai and C. Roos, Primal-dual interior-point algorithms for semidefinite optimization based on a simple kernel function,, Journal of Mathematical Modelling and Algorithms, 4 (2005), 409. Google Scholar |
[21] |
G. Q. Wang and D. T. Zhu., A unified kernel function approach to primal-dual interior-point algorithms for convex quadratic SDO,, Numerical Algorithms, 57 (2011), 537.
doi: 10.1007/s11075-010-9444-3. |
[22] |
L. P. Zhang, Y. H. Xu and Z. J. Jin, An efficient algorithm for convex quadratic semidefinite optimization,, Numerical Algebra, 2 (2012), 129.
doi: 10.3934/naco.2012.2.129. |
[23] |
M. W. Zhang, A large-update interior-point algorithm for convex quadratic semidefinite optimization based on a new kernel function,, Acta Mathematica Sinica (English Series), 28 (2012), 2313.
doi: 10.1007/s10114-012-0194-0. |
[24] |
Y. Zhang, On extending some primal-dual interior-point algorithms from linear programming to semidefinite programming,, SIAM Journal on Optimization, 8 (1998), 365.
doi: 10.1137/S1052623495296115. |
show all references
References:
[1] |
M. Achache and L. Guerra, A full Nesterov-Todd step feasible primal-dual interior-point algorithm for convex quadratic semidefinite optimization,, Applied Mathematics and Computation, 231 (2014), 581.
doi: 10.1016/j.amc.2013.12.070. |
[2] |
Y. Q. Bai, M. El Ghami and C. Roos, A comparative study of kernel functions for primal-dual interior-point algorithms in linear optimization,, SIAM Journal on Optimization, 15 (2004), 101.
doi: 10.1137/S1052623403423114. |
[3] |
X. Z. Cai, G. Q. Wang, M. El Ghami and Y. J. Yue, Complexity analysis of primal-dual interior-point methods for linear optimization based on a parametric kernel function with a trigonometric barrier term,, Abstract and Applied Analysis, 2014 (2014).
doi: 10.1155/2014/710158. |
[4] |
B. K. Choi. and G. M. Lee, On complexity analysis of the primal-dual interior-point method for semidefinite optimization problem based on a new proximity function,, Nonlinear Analysis, 71 (2009), 2628.
doi: 10.1016/j.na.2009.05.078. |
[5] |
Zs. Darvay, New interior point algorithms in linear programming,, Advanced Modeling and Optimization, 5 (2003), 51.
|
[6] |
E. De Klerk, Aspects of Semidefinite Programming: Interior Point Algorithms and Selected Applications,, Kluwer Academic Publishers, (2002).
doi: 10.1007/b105286. |
[7] |
M. El Ghami, Z. A. Guennounb, S. Bouali and T. Steihaug, Interior-point methods for linear optimization based on a kernel function with a trigonometric barrier term,, Journal of Computational and Applied Mathematics, 236 (2012), 3613.
doi: 10.1016/j.cam.2011.05.036. |
[8] |
M. El Ghami, C. Roos and T. Steihaug, A generic primal-dual interior-point method for semidefinite optimization based on a new class of kernel functions,, Optimization Methods & Software, 25 (2010), 387.
doi: 10.1080/10556780903239048. |
[9] |
R. A. Horn and C. R. Johnson, Topics in Matrix Analysis,, Cambridge University Press, (1991).
doi: 10.1017/CBO9780511840371. |
[10] |
B. Kheirfam, Simplified infeasible interior-point algorithm for SDO using full Nesterov-Todd step,, Numerical Algorithms, 59 (2012), 589.
doi: 10.1007/s11075-011-9506-1. |
[11] |
M. Kojima, M. Shida and S. Shindoh, Local convergence of predictor-corrector infeasible-interior-point method for SDPs and SDLCPs,, Mathematical Programming, 80 (1998), 129.
doi: 10.1007/BF01581723. |
[12] |
H. W. Liu, C. H. Liu and X. M. Yang, New complexity analysis of a Mehrotra-type predictor-corrector algorithm for semidefinite programming,, Optimization Methods & Software, 28 (2013), 1179.
doi: 10.1080/10556788.2012.679270. |
[13] |
H. Mansouri and C. Roos, A new full-Newton step O(n) infeasible interior-point algorithm for semidefinite optimization,, Numerical Algorithms, 52 (2009), 225.
doi: 10.1007/s11075-009-9270-7. |
[14] |
J. Peng, C. Roos and T. Terlaky, Self-regular functions and new search directions for linear and semidefinite optimization,, Mathematical Programming, 93 (2002), 129.
doi: 10.1007/s101070200296. |
[15] |
M. R. Peyghami, An interior-point approach for semidefinite optimization using new proximity functions,, Asia-Pacific Journal of Operational Research, 26 (2009), 365.
doi: 10.1142/S0217595909002250. |
[16] |
M. R. Peyghami and S. F. Hafshejani, Complexity analysis of an interior-point algorithm for linear optimization based on a new proximity function,, Numerical Algorithms, 67 (2014), 33.
doi: 10.1007/s11075-013-9772-1. |
[17] |
M. R. Peyghami, S. F. Hafshejani and L. Shirvani, Complexity of interior-point methods for linear optimization based on a new trigonometric kernel function,, Journal of Computational and Applied Mathematics, 255 (2014), 74.
doi: 10.1016/j.cam.2013.04.039. |
[18] |
C. Roos, T. Terlaky and J.-Ph. Vial, Theory and Algorithms for Linear Optimization,, Springer, (2005). Google Scholar |
[19] |
G. Q. Wang and Y. Q. Bai, A new primal-dual path-following interior-point algorithm for semidefinite optimization,, Journal of Mathematical Analysis and Applications, 353 (2009), 339.
doi: 10.1016/j.jmaa.2008.12.016. |
[20] |
G. Q. Wang, Y. Q. Bai and C. Roos, Primal-dual interior-point algorithms for semidefinite optimization based on a simple kernel function,, Journal of Mathematical Modelling and Algorithms, 4 (2005), 409. Google Scholar |
[21] |
G. Q. Wang and D. T. Zhu., A unified kernel function approach to primal-dual interior-point algorithms for convex quadratic SDO,, Numerical Algorithms, 57 (2011), 537.
doi: 10.1007/s11075-010-9444-3. |
[22] |
L. P. Zhang, Y. H. Xu and Z. J. Jin, An efficient algorithm for convex quadratic semidefinite optimization,, Numerical Algebra, 2 (2012), 129.
doi: 10.3934/naco.2012.2.129. |
[23] |
M. W. Zhang, A large-update interior-point algorithm for convex quadratic semidefinite optimization based on a new kernel function,, Acta Mathematica Sinica (English Series), 28 (2012), 2313.
doi: 10.1007/s10114-012-0194-0. |
[24] |
Y. Zhang, On extending some primal-dual interior-point algorithms from linear programming to semidefinite programming,, SIAM Journal on Optimization, 8 (1998), 365.
doi: 10.1137/S1052623495296115. |
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